Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2022-08-02 12:04:09	ga_s2am_ard_3-2-1_50KKA_2022-08-02_final.stac-item
2022-08-02 12:04:09	ga_s2am_ard_3-2-1_49KHR_2022-08-02_final.stac-item
2022-08-02 12:04:24	ga_s2am_ard_3-2-1_50KKV_2022-08-02_final.stac-item
2022-08-02 12:04:28	ga_s2am_ard_3-2-1_49KGQ_2022-08-02_final.stac-item
2022-08-02 12:04:37	ga_s2am_ard_3-2-1_49KGP_2022-08-02_final.stac-item
2022-08-02 12:04:53	ga_s2am_ard_3-2-1_50JKT_2022-08-02_final.stac-item
2022-08-02 12:04:56	ga_s2am_ard_3-2-1_49JGN_2022-08-02_final.stac-item
2022-08-02 12:05:04	ga_s2am_ard_3-2-1_50JLS_2022-08-02_final.stac-item
2022-08-02 12:05:11	ga_s2am_ard_3-2-1_49JGM_2022-08-02_final.stac-item
2022-08-02 12:05:48	ga_s2am_ard_3-2-1_50JLP_2022-08-02_final.stac-item
2022-08-02 12:05:54	ga_s2am_ard_3-2-1_49JGJ_2022-08-02_final.stac-item
2022-08-02 12:06:06	ga_s2am_ard_3-2-1_50JKN_2022-08-02_final.stac-item
2022-08-02 12:06:24	ga_s2am_ard_3-2-1_50JLL_2022-08-02_final.stac-item
2022-08-03 11:34:54	ga_s2am_ard_3-2-1_51JVM_2022-08-03_final.stac-item
2022-08-03 11:35:08	ga_s2am_ard_3-2-1_51JVL_2022-08-03_final.stac-item
2022-08-03 11:35:26	ga_s2am_ard_3-2-1_51JUK_2022-08-03_final.stac-item
2022-08-03 11:35:29	ga_s2am_ard_3-2-1_51JTK_2022-08-03_final.stac-item
2022-08-03 11:35:30	ga_s2am_ard_3-2-1_51JWJ_2022-08-03_final.stac-item
2022-08-03 11:35:41	ga_s2am_ard_3-2-1_51JUJ_2022-08-03_final.stac-item
2022-08-03 11:35:48	ga_s2am_ard_3-2-1_50JQP_2022-08-03_final.stac-item
2022-08-03 11:35:52	ga_s2am_ard_3-2-1_51JVH_2022-08-03_final.stac-item
2022-08-03 11:36:01	ga_s2am_ard_3-2-1_50JQN_2022-08-03_final.stac-item
2022-08-05 12:14:05	ga_s2am_ard_3-2-1_50KKA_2022-08-05_final.stac-item
2022-08-05 12:14:24	ga_s2am_ard_3-2-1_49KGQ_2022-08-05_final.stac-item
2022-08-05 12:14:38	ga_s2am_ard_3-2-1_49KGP_2022-08-05_final.stac-item
2022-08-05 12:14:52	ga_s2am_ard_3-2-1_49JGN_2022-08-05_final.stac-item
2022-08-05 12:14:56	ga_s2am_ard_3-2-1_49JFN_2022-08-05_final.stac-item
2022-08-06 11:45:22	ga_s2am_ard_3-2-1_50JNR_2022-08-06_final.stac-item
2022-08-06 11:45:25	ga_s2am_ard_3-2-1_51JTK_2022-08-06_final.stac-item
2022-08-06 11:45:43	ga_s2am_ard_3-2-1_50JQP_2022-08-06_final.stac-item
2022-08-06 11:45:47	ga_s2am_ard_3-2-1_50JPP_2022-08-06_final.stac-item
2022-08-06 11:46:05	ga_s2am_ard_3-2-1_50JNN_2022-08-06_final.stac-item
2022-08-09 11:55:03	ga_s2am_ard_3-2-1_50JNS_2022-08-09_final.stac-item
2022-08-09 11:55:53	ga_s2am_ard_3-2-1_50JLP_2022-08-09_final.stac-item
2022-08-09 11:56:05	ga_s2am_ard_3-2-1_50JMN_2022-08-09_final.stac-item
2022-08-10 11:25:03	ga_s2am_ard_3-2-1_51JYL_2022-08-10_final.stac-item
2022-08-10 11:25:15	ga_s2am_ard_3-2-1_51JVL_2022-08-10_final.stac-item
2022-08-10 11:25:40	ga_s2am_ard_3-2-1_51JWJ_2022-08-10_final.stac-item
2022-08-10 11:25:57	ga_s2am_ard_3-2-1_51JVH_2022-08-10_final.stac-item
2022-08-12 12:04:11	ga_s2am_ard_3-2-1_50KKA_2022-08-12_final.stac-item
2022-08-12 12:04:11	ga_s2am_ard_3-2-1_49KHR_2022-08-12_final.stac-item
2022-08-12 12:04:25	ga_s2am_ard_3-2-1_50KKV_2022-08-12_final.stac-item
2022-08-12 12:04:30	ga_s2am_ard_3-2-1_49KGQ_2022-08-12_final.stac-item
2022-08-12 12:04:43	ga_s2am_ard_3-2-1_49KGP_2022-08-12_final.stac-item
2022-08-12 12:04:55	ga_s2am_ard_3-2-1_50JKT_2022-08-12_final.stac-item
2022-08-12 12:04:58	ga_s2am_ard_3-2-1_49JGN_2022-08-12_final.stac-item
2022-08-12 12:05:41	ga_s2am_ard_3-2-1_49JGK_2022-08-12_final.stac-item
2022-08-12 12:05:50	ga_s2am_ard_3-2-1_50JLP_2022-08-12_final.stac-item
2022-08-12 12:05:56	ga_s2am_ard_3-2-1_49JGJ_2022-08-12_final.stac-item
2022-08-13 11:34:55	ga_s2am_ard_3-2-1_51JVM_2022-08-13_final.stac-item
2022-08-13 11:35:10	ga_s2am_ard_3-2-1_51JVL_2022-08-13_final.stac-item
2022-08-13 11:35:28	ga_s2am_ard_3-2-1_51JUK_2022-08-13_final.stac-item
2022-08-13 11:35:31	ga_s2am_ard_3-2-1_51JTK_2022-08-13_final.stac-item
2022-08-13 11:35:31	ga_s2am_ard_3-2-1_51JWJ_2022-08-13_final.stac-item
2022-08-13 11:35:42	ga_s2am_ard_3-2-1_51JUJ_2022-08-13_final.stac-item
2022-08-13 11:35:49	ga_s2am_ard_3-2-1_50JQP_2022-08-13_final.stac-item
2022-08-13 11:35:53	ga_s2am_ard_3-2-1_51JVH_2022-08-13_final.stac-item
2022-08-13 11:36:03	ga_s2am_ard_3-2-1_50JQN_2022-08-13_final.stac-item
2022-08-15 12:14:06	ga_s2am_ard_3-2-1_50KKA_2022-08-15_final.stac-item
2022-08-15 12:14:07	ga_s2am_ard_3-2-1_49KHR_2022-08-15_final.stac-item
2022-08-15 12:14:11	ga_s2am_ard_3-2-1_49KGR_2022-08-15_final.stac-item
2022-08-15 12:14:20	ga_s2am_ard_3-2-1_50KKV_2022-08-15_final.stac-item
2022-08-15 12:14:25	ga_s2am_ard_3-2-1_49KGQ_2022-08-15_final.stac-item
2022-08-15 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-08-15_final.stac-item
2022-08-15 12:14:54	ga_s2am_ard_3-2-1_49JGN_2022-08-15_final.stac-item
2022-08-15 12:14:58	ga_s2am_ard_3-2-1_49JFN_2022-08-15_final.stac-item
2022-08-15 12:15:08	ga_s2am_ard_3-2-1_49JGM_2022-08-15_final.stac-item
2022-08-15 12:15:32	ga_s2am_ard_3-2-1_49JGK_2022-08-15_final.stac-item
2022-08-16 11:45:24	ga_s2am_ard_3-2-1_50JNR_2022-08-16_final.stac-item
2022-08-16 11:45:27	ga_s2am_ard_3-2-1_51JTK_2022-08-16_final.stac-item
2022-08-16 11:45:48	ga_s2am_ard_3-2-1_50JPP_2022-08-16_final.stac-item
2022-08-16 11:45:59	ga_s2am_ard_3-2-1_50JQN_2022-08-16_final.stac-item
2022-08-16 11:46:06	ga_s2am_ard_3-2-1_50JNN_2022-08-16_final.stac-item
2022-08-19 11:55:04	ga_s2am_ard_3-2-1_50JNS_2022-08-19_final.stac-item
2022-08-19 11:55:10	ga_s2am_ard_3-2-1_50JLS_2022-08-19_final.stac-item
2022-08-19 11:55:19	ga_s2am_ard_3-2-1_50JNR_2022-08-19_final.stac-item
2022-08-19 11:55:39	ga_s2am_ard_3-2-1_50JPP_2022-08-19_final.stac-item
2022-08-19 11:55:54	ga_s2am_ard_3-2-1_50JLP_2022-08-19_final.stac-item
2022-08-19 11:56:02	ga_s2am_ard_3-2-1_50JNN_2022-08-19_final.stac-item
2022-08-20 11:24:42	ga_s2am_ard_3-2-1_51JXN_2022-08-20_final.stac-item
2022-08-20 11:25:16	ga_s2am_ard_3-2-1_51JVL_2022-08-20_final.stac-item
2022-08-20 11:25:40	ga_s2am_ard_3-2-1_51JWJ_2022-08-20_final.stac-item
2022-08-20 11:25:58	ga_s2am_ard_3-2-1_51JVH_2022-08-20_final.stac-item
2022-08-22 12:04:11	ga_s2am_ard_3-2-1_50KKA_2022-08-22_final.stac-item
2022-08-22 12:04:12	ga_s2am_ard_3-2-1_49KHR_2022-08-22_final.stac-item
2022-08-22 12:04:55	ga_s2am_ard_3-2-1_50JKT_2022-08-22_final.stac-item
2022-08-22 12:04:59	ga_s2am_ard_3-2-1_49JGN_2022-08-22_final.stac-item
2022-08-22 12:05:06	ga_s2am_ard_3-2-1_50JLS_2022-08-22_final.stac-item
2022-08-22 12:05:13	ga_s2am_ard_3-2-1_49JGM_2022-08-22_final.stac-item
2022-08-22 12:05:21	ga_s2am_ard_3-2-1_49JFM_2022-08-22_final.stac-item
2022-08-22 12:05:50	ga_s2am_ard_3-2-1_50JLP_2022-08-22_final.stac-item
2022-08-23 11:34:56	ga_s2am_ard_3-2-1_51JVM_2022-08-23_final.stac-item
2022-08-23 11:35:10	ga_s2am_ard_3-2-1_51JVL_2022-08-23_final.stac-item
2022-08-23 11:35:31	ga_s2am_ard_3-2-1_51JWJ_2022-08-23_final.stac-item
2022-08-23 11:35:43	ga_s2am_ard_3-2-1_51JUJ_2022-08-23_final.stac-item
2022-08-23 11:35:50	ga_s2am_ard_3-2-1_50JQP_2022-08-23_final.stac-item
2022-08-25 12:14:07	ga_s2am_ard_3-2-1_50KKA_2022-08-25_final.stac-item
2022-08-25 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-08-25_final.stac-item
2022-08-25 12:14:54	ga_s2am_ard_3-2-1_49JGN_2022-08-25_final.stac-item
2022-08-26 11:45:27	ga_s2am_ard_3-2-1_51JTK_2022-08-26_final.stac-item

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years